This study introduces a novel Groundwater Flooding Risk Assessment (GFRA) model to evaluate risks associated with groundwater flooding (GF), a globally significant hazard often overshadowed by surface water flooding. GFRA utilizes a conditional probability function considering critical factors, including topography, ground slope, and land use-recharge to generate a risk assessment map. Additionally, the study evaluates the return period of GF events (GFRP) by fitting annual maxima of groundwater levels to probability distribution functions (PDFs). Approximately 57% of the pilot area falls within high and critical GF risk categories, encompassing residential and recreational areas. Urban sectors in the north and east, containing private buildings, public centers, and industrial structures, exhibit high risk, while developing areas and agricultural lands show low to moderate risk. This serves as an early warning for urban development policies. The Generalized Extreme Value (GEV) distribution effectively captures groundwater level fluctuations. According to the GFRP model, about 21% of the area, predominantly in the city's northeast, has over 50% probability of GF exceedance (1 to 2-year return period). Urban outskirts show higher return values (> 10 years). The model's predictions align with recorded flood events (90% correspondence). This approach offers valuable insights into GF threats for vulnerable locations and aids proactive planning and management to enhance urban resilience and sustainability.

Using the rank scale rule, taking 47 major port cities in China from 2001 to 2015 as research samples, this paper discusses the rank scale characteristics and hierarchical structure of coastal port city system from a multi-functional perspective, and divides the coupling type of multi-functional development based on shipping logistics. The research shows that: 1) from 2001 to 2015, the scale-free area of manufacturing function order scale distribution in the coastal port city system appeared bifractal structure, the hierarchical segmentation characteristics appeared, and the other functions were single fractal; From the perspective of long-term evolution, only the order and scale distribution of shipping logistics function has developed from centralization to equilibrium, while the business function, manufacturing function (scale-free region I), modern service function and population distribution function are in a centralized situation. 2) The hierarchical structure of coastal port city system has gradually changed from pyramid structure to spindle structure, and generally formed five levels: national hub, regional hub, regional sub center, regional node and local node. 3) From the perspective of multi-functional coupling types, the traditional functions of port cities are generally ahead, while the high-end service functions lag behind, and the improvement speed of urban functions is slow and tends to be flat, indicating that the multi-functional development of China’s coastal port cities is still at a low level, and the industrial system structure needs to be further optimized. 4) From the perspective of port cities at different levels, the functions of regional hub cities and regional sub central cities are in the stage of rapid growth; regional and local node cities are still in the growth stage of traditional functions such as industry and commerce.

The semi-arid is a climate characterized by precipitation that is. insufficient to maintain crops and where evaporation often exceeds rainfall. Vegetation is one of the most sensitive indicators of environmental changes understanding the patterns of biodiversity distribution and what influences them is a fundamental pre-requisite for effective conservation and sustainable utilization of biodiversity. In this study. our focus was on examining the vegetation diversity in the semi-arid region of Tebessa. which falls within the Eastern Saharan Atlas domain in North Africa’s semi-arid zone. Plants were sampled at 15 sites distributed across the study area. The quadrat method was used to conduct floral surveys. The sampling area of each sample was 100 square meters 10 m × 10 m (quadrat). Each quadrat was measured for species richness (number of species). abundance (number of individuals). and Richness generic (plant cover). Based on the floristic research. 48 species were found. classified into 21 families. with Asteraceae accounting for 34.69% of the species and Poaceae accounting for 14.28%.

This study examines the spatial distribution of consumption competitiveness and carrying capacity across regions, exploring their interrelationship and implications for sustainable regional development. An evaluation index system is constructed for both consumption competitiveness and carrying capacity using a range of economic, social, and environmental indicators. We apply this framework to regional data in China and analyze the resultant spatial patterns. The findings reveal significant regional disparities: areas with strong consumption competitiveness are often concentrated in economically developed regions, while high carrying capacity is notable in less populated or resource-rich areas. Notably, a mismatch emerges in some regions—high consumer demand is not always supported by adequate carrying capacity, and vice versa. These disparities highlight potential sustainability challenges and opportunities. In the discussion, we address reasons behind the spatial mismatch and propose policy implications to better align consumer market growth with regional resource and environmental capacity. The paper concludes that integrating consumption-driven growth strategies with carrying capacity considerations is essential for balanced and sustainable regional development.

Based on the research on 31 provincial-level administrative regions at the end of 2022, we used the geographic concentration index, geographic imbalance index, SPSS and ARCGIS spatial analysis techniques to study the spatial distribution, distribution factor correlation, and accessibility of national 5A-level scenic spots. The research results show that the overall distribution of my country's 5A-level scenic spots is unbalanced, with a low degree of concentration, showing a pattern of denseness in the east and sparseness in the west, with large inter-provincial differences. The density of traffic highways is positively correlated with the distribution density of 5A-level scenic spots. The traffic lines in the central and eastern regions are dense, and there are a large number of 5A-level scenic spots, especially the Beijing-Tianjin-Hebei region, the Yangtze River Delta region, and the middle and lower reaches of the Yangtze River and Yellow River. Therefore, the spatial distribution of China's 5A-level tourist attractions is mainly affected by the interaction of economic, transportation and social factors, among which GDP, transportation network and attraction of scenic spots are the most critical factors. These research results can provide a reference for optimizing the spatial layout of China's scenic resources and promoting regional socio-economic development.